Tag: mvp

I’ve been giving some more thought to the idea of “good enough” as one of the criteria for defining minimum viable/valuable products. I still stand by everything I wrote in my original “The Value of ‘Good Enough’” article. What’s different is that I’ve started to use the phrase “good enough for now.” Reason being, the phrase “good enough” seems to imply an end state. If it is early in a project, people generally have a problem with that. They have some version of an end state that is a significant mismatch with the “good enough” product today. The idea of settling for “good enough” at this point makes it difficult for them to know when to stop work on an interim phase and collect feedback.

“Good enough for now” implies there is more work to be done and the product isn’t in some sort of finished state that they’ll have to settle for. I’m finding that I can more easily gain agreement that a story is finished and get people to move forward to the next “good enough for now” by including the time qualifier.

An experienced scrum master describes their work cycles as going “from being very busy during sprint end/start weeks to be [sic] very bored.” While this scrum master works very hard to fill in the gaps with 1:1’s with the team members and providing regular training opportunities, they nonetheless ask the question, “Does anyone have any suggestions of things I am maybe not doing that I should be doing?” One response included the following:

“Now, it could be that you have worked to create a hyper-performing team and there is no further room for improvement. A measure of this is that velocity (or similar metric) has increased by an order of magnitude in the last year.

However, the most likely scenario is that you and your team have become ‘comfortable’ and velocity has not increased significantly in the last few Sprints and/or there is a high variance in velocity.”

This reflects a common misunderstanding of “velocity” and its confusion with “acceleration.” (It also reflects the “more is better” and “winners vs losers” thinking derived from the scrum sports metaphor and points as a way of keeping score. I’ve written about that elsewhere.) Neither does the commenter understand what “order of magnitude” means. A velocity that increases by an order of magnitude in a year isn’t a velocity, it’s an acceleration. That’s a bad thing. This wouldn’t be a “hyper-performing” team. This would be a team headed for a crash as a continual acceleration in story points completed is untenable. More and more points each sprint isn’t the goal of scrum. A product owner cannot predict when their team might complete a feature or a project if the delivery of work is accelerating throughout the project.

Assuming a typical project, something that continues for a year or more, the team and the project will eventually crash as they’ve been pressured to work more and more hours and cut more and more corners in the interests of completing more and more points. The accumulation of bugs, small and large, will slow progress. Team fatigue will increase and moral decrease, resulting in turn-over and further delays. In common parlance, this is referred to as a “death march.”

Strictly speaking, velocity is some displacement over time. In the case of scrum, it is the number of story points completed in a sprint. We’ve “displace” some number of story points from being “not done” to “done.” By itself, a single sprint’s velocity isn’t particularly useful. Looking at the velocity of a number of successive sprints, however, is useful. There are two pieces of information from looking at successive sprint velocities that, when considered together, can reveal useful aspects of how well a team is performing or not. The first is the average over the previous 5 to 8 sprints, a rolling average. As a yard stick, this can provide a measure of predictability. Using this average, a product owner can make a rough calculation for how many sprints remain before completing components or the project based on the story point information in the product backlog.

The measure of confidence for this prediction would come from an analysis of the variance demonstrated in the sprint velocity values over time. Figures 1 and 2 show the distinction between the value provided by a rolling average and the value provided by the variance in values over time.

Figure 1

Figure 2

In both cases the respective teams have an average velocity of 21 points per sprint. However, the variability in the values over time show that the team in Figure 1 would have a much higher level of confidence in any predictions based on their past performance than the team shown in Figure 2.

What matters is the trend, each sprint’s velocity over a number of sprints. The steady completion of story points (i.e. work) sprint to sprint is the desirable goal. Another way to say this is that a steady velocity makes it possible to predict project delivery dates. In real life, there will be a variance (up and down) of sprint velocity over time and the goal is to guide the project such that this variance is within a manageable range.

If a team were to set as its goal an increase in the number of story points completed from sprint to sprint then their performance chart might initially look like Figure 3.

Figure 3

Such a pace is unsustainable and eventually the team burns out. Fatigue, decreased moral, and overall dissatisfaction with the project cause team members to quit and progress grinds to a halt. The fallout of such a collapse is likely to include the buildup of significant technical debt and code errors as the run-up to the crescendo forced team members to cut corners, take shortcuts, and otherwise compromise the quality of their effort. [1] The resulting performance chart would look something like Figure 4.

Figure 4

All that said, I grant that there is merit in coaching teams to make reasonable improvements in their overall sprint performance. An increase in the overall average velocity might be one way to measure this. However, to press the team into achieving an order of magnitude increase in performance is a fools errand and more than likely to end in disaster for the team and the project.

Conceptually, the idea of a minimum viable product (MVP) is easy to grasp. Early in a project, it’s a deliverable that reflects some semblance to the final product such that it’s barely able to stand on it’s own without lots of hand-holding and explanation for the customer’s benefit. In short, it’s terrible, buggy, and unstable. By design, MVPs lack features that may eventually prove to be essential to the final product. And we deliberately show the MVP to the customer!

We do this because the MVP is the engine that turns the build-measure-learn feedback loop. The key here is the “learn” phase. The essential features to the final product are often unclear or even unknown early in a project. Furthermore, they are largely undefinable or unknowable without multiple iterations through the build-measure-learn feedback cycle with the customer early in the process.

So early MVPs aren’t very good. They’re also not very expensive. This, too, is by design because an MVP’s very raison d’être is to test the assumptions we make early on in a project. They are low budget experiments that follow from a simple strategy:

State the good faith assumptions about what the customer wants and needs.

Describe the tests the MVP will satisfy that are capable of measuring the MVP’s impact on the stated assumptions.

Build an MVP that tests the assumptions.

Evaluate the results.

If the assumptions are not stated and the tests are vague, the MVP will fail to achieve it’s purpose and will likely result in wasted effort.

The “product” in “minimum viable product” can be almost anything: a partial or early design flow, a wireframe, a collection of simulated email exchanges, the outline to a user guide, a static screen mock-up, a shell of screen panels with placeholder text that can nonetheless be navigated – anything that can be placed in front of a customer for feedback qualifies as an MVP. In other words, a sprint can contain multiple MVPs depending on the functional groups involved with the sprint and the maturity of the project. As the project progresses, the individual functional group MVPs will begin to integrate and converge on larger and more refined MVPs, each gaining in stability and quality.

MVPs are not an end unto themselves. They are tangible evidence of the development process in action. The practice of iteratively developing MVPs helps develop to skill of rapid evaluation and learning among product owners and agile delivery team members. A buggy, unstable, ugly, bloated, or poorly worded MVP is only a problem if it’s put forward as the final product. The driving goal behind iterative MVPs is not perfection, rather it is to support the process of learning what needs to be developed for the optimal solution that solves the customer’s problems.

“Unlike a prototype or concept test, an MVP is designed not just to answer product design or technical questions. Its goal is to test fundamental business hypotheses.” – Eric Ries, The Lean Startup

So how might product owners and Agile teams begin to get a handle on defining an MVP? There are several questions the product owner and team can ask of themselves, in light of the product backlog, that may help guide their focus and decisions. (Use of the following term “stakeholders” can mean company executives or external customers.)

Identify the likely set of stakeholders who will be attending the sprint review. What will these stakeholders need to see so that they can offer valuable feedback? What does the team need to show in order to spark the most valuable feedback from the stakeholders?

What expectations have been set for the stakeholders?

Is the distinction clear between what the stakeholders want vs what they need?

Is the distinction clear between high and low value? Is the design cart before the value horse?

What are the top two features or functions the stakeholders will be expecting to see? What value – to the stakeholders – will these features or functions deliver?

Will the identified features or functions provide long term value or do they risk generating significant rework down the road?

Are the identified features or functions leveraging code, content, or UI/UX reuse?

Recognizing an MVP – Less is More

Since an MVP can be almost anything, it is perhaps easier to begin any conversation about MVPs by touching on the elements missing from an MVP.

An MVP is not a quality product. Using any generally accepted definition of “quality” in the marketplace, an MVP will fail on all accounts. Well, on most accounts. The key is to consider relative quality. At the beginning of a sprint, the standards of quality for an MVP are framed by the sprint goals and objectives. If it meets those goals, the team has successfully created a quality MVP. If measured against the external marketplace or the quality expectations of the customer, the MVP will almost assuredly fail inspection.

Your MVPs will probably be ugly, especially at first. They will be missing features. They will be unstable. Build them anyway. Put them in front of the customer for feedback. Learn. And move on to the next MVP. Progressively, they will begin to converge on the final product that is of high quality in the eyes of the customer. MVPs are the stepping stones that get you across the development stream and to the other side where all is sunny, beautiful, and stable. (For more information on avoiding the trap of presupposing what a customer means by quality and value, see “The Value of ‘Good Enough’“)

An MVP is not permanent. Agile teams should expect to throw away several, maybe even many, MVPs on their way to the final product. If they aren’t, then it is probable they are not learning what they need to about what the customer actually wants. In this respect, waste can be a good, even important thing. The driving purpose of the MVP is to rapidly develop the team’s understanding of what the customer needs, the problems they are expecting to have solved, and the level of quality necessary to satisfy each of these goals.

MVPs are not the truth. They are experiments meant to get the team to the truth. By virtue of their low-quality, low-cost nature, MVPs quickly shake out the attributes to the solution the customer cares about and wants. The solid empirical foundation they provide is orders of magnitude more valuable to the Agile team than any amount of speculative strategy planning or theoretical posturing.

Any company interested in being successful, whether offering a product or service, promises quality to its customers. Those that don’t deliver, die away. Those that do, survive. Those that deliver quality consistently, thrive. Seems like easy math. But then, 1 + 1 = 2 seems like easy math until you struggle through the 350+ pages Whitehead and Russell1 spent on setting up the proof for this very equation. Add the subjective filters for evaluating “quality” and one is left with a measure that can be a challenge to define in any practical way.

Math aside, when it comes to quality, everyone “knows it when they see it,” usually in counterpoint to a decidedly non-quality experience with a product or service. The nature of quality is indeed chameleonic – durability, materials, style, engineering, timeliness, customer service, utility, aesthetics – the list of measures is nearly endless. Reading customer reviews can reveal a surprising array of criteria used to evaluate the quality for a single product.

The view from within the company, however, is even less clear. Businesses often believe they know quality when they see it. Yet that belief is often predicate on how the organization defines quality, not how their customers define quality. It is a definition that is frequently biased in ways that accentuate what the organization values, not necessarily what the customer values.

Organization leaders may define quality too high, such that their product or service can’t be priced competitively or delivered to the market in a timely manner. If the high quality niche is there, the business might succeed. If not, the business loses out to lower priced competitors that deliver products sooner and satisfy the customer’s criteria for quality (see Figure 1).

Figure 1. Quality Mismatch I

Certainly, there is a case that can be made for providing the highest quality possible and developing the business around that niche. For startups and new product development, this may not be be best place to start.

On the other end of the spectrum, businesses that fall short of customer expectations for quality suffer incremental, or in some cases catastrophic, reputation erosion. Repairing or rebuilding a reputation for quality in a competitive market is difficult, maybe even impossible (see Figure 2).

Figure 2. Quality Mismatch II

The process for defining quality on the company side of the equation, while difficult, is more or less deliberate. Not so on the customer side. Customers often don’t know what they mean by “quality” until they have an experience that fails to meet their unstated, or even unknown, expectations. Quality savvy companies, therefore, invest in understanding what their customers mean by “quality” and plan accordingly. Less guess work, more effort toward actual understanding.

Furthermore, looking to what the competition is doing may not be the best strategy. They may be guessing as well. It may very well be that the successful quality strategy isn’t down the path of adding more bells and whistles that market research and focus groups suggest customers want. Rather, it may be that improvements in existing features and services are more desirable.

Focus on being clear about whether or not potential customers value the offered solution and how they define value. When following an Agile approach to product development, leveraging minimum viable product definitions can help bring clarity to the effort. With customer-centric benchmarks for quality in hand, companies are better served by first defining quality in terms of “good enough” in the eyes of their customers and then setting the internal goal a little higher. This will maximize internal resources (usually time and money) and deliver a product or service that satisfies the customer’s idea of “quality.”

Case in point: Several months back, I was assembling several bar clamps and needed a set of cutting tools used to put the thread on the end of metal pipes – a somewhat exotic tool for a woodworker’s shop. Shopping around, I could easily drop $300 for a five star “professional” set or $35 for a set that was rated to be somewhat mediocre. I’ve gone high end on many of the tools in my shop, but in this case the $35 set was the best solution for my needs. Most of the negative reviews revolved around issues with durability after repeated use. My need was extremely limited and the “valuable and good enough” threshold was crossed at $35. The tool set performed perfectly and more than paid for itself when compared with the alternatives, whether that be a more expensive tool or my time to find a local shop to thread the pipes for me. This would not have been the case for a pipefitter or someone working in a machine shop.

By understanding where the “good enough and valuable” line is, project and organization leaders are in a better position to evaluate the benefits of incremental improvements to core products and services that don’t break the bank or burn out the people tasked with delivering the goods. Of course, determining what is “good enough” depends on the end goal. Sending a rover to Mars, “good enough” had better be as near to perfection as possible. Threading a dozen pipes for bar clamps used in a wood shop can be completed quite successful with low quality tools that are “good enough” to get the job done.

References

1Volume 1 of Principia Mathematica by Alfred North Whitehead and Bertrand Russell (Cambridge University Press, page 379). The proof was actually not completed until Volume 2.

Do you see white dots embedded within the grid connected by diagonal white lines? If you do, try and ignore them. Chances are, your brain won’t let you even though the white circles and diagonal lines don’t exist. Their “thereness” is created by the thin black lines. By carefully drawing a simple repetitive pattern of black lines, your brain has filled in the void and enhanced the image with white dots and diagonal white lines. You cannot not do this. This cognitive process is important to be aware of if you are a product owner because both your agile delivery team members and clients will run this program without fail.

Think of the black lines as the minimum viable product definition for one of your sprints. When shown to your team or your client, they will naturally fill the void for what’s next or what’s missing. Maybe as a statement, most likely as a question. But what if the product owner defined the minimum viable product further and presented, metaphorically, something like this:

By removing the white space from the original image there are fewer possibilities for your team and the client to explore. We’ve reduced their response to our proposed solution to a “yes” or “no” and in doing so have started moving down the path of near endless cycles of the product owner guessing what the client wants and the agile delivery team guessing what the product owner wants. Both the client and the team will grow increasingly frustrated at the lack of progress. Played out too long, the client is likely to doubt our skills and competency at finding a solution.

On the other hand, by strategically limiting the information presented in the minimum viable product (or effort, if you like) we invite the client and the agile delivery team to explore the white space. This will make them co-creators of the solution and more fully invested in its success. Since they co-created the solution, they are much more likely to view the solution as brilliant, perfect, and the shiniest of shiny objects.

I can’t remember where I heard or read this, but in the first image the idea is that the black lines are you talking and the white spaces are you listening.